{
 "cells": [
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Avoid Negative Predictions in Forecasting\n",
    "\n",
    "When training a forecasting model, even if none of the training observations are negative, some predictions may turn out to be negative. This is quite common when trying to predict attendance, sales, or rainfall, among other things. To avoid this, it is possible to use the following approaches:\n",
    "\n",
    "+ Use a <i>log+K</i> transformation to always have positive values in the transformed time series. <i>K</i> is a positive integer to avoid the undefinability of the $log(x)$ function at 0. Despite the simplicity of the approach, one must be aware that [some caveats may arise](https://florianwilhelm.info/2020/05/honey_i_shrunk_the_target_variable/) depending on the metric we use to optimize our models.\n",
    "\n",
    "+ Use a different link function in the models. The link function provides the relationship between the linear predictor and the expected value of the response variable. When using machine learning models, several algorithms support different objective functions to account for this situation. For example, when predicting the number of visitors, one can use `count:poisson` in XGBoost or LightGBM as well as gamma regression if the target is always strictly positive.\n",
    "\n",
    "The following tutorial will explore both possibilities."
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Libraries and data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Libraries\n",
    "# ==============================================================================\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from sklearn.linear_model import Ridge, GammaRegressor\n",
    "from sklearn.preprocessing import FunctionTransformer\n",
    "from sklearn.metrics import mean_squared_error\n",
    "from xgboost import XGBRegressor\n",
    "from skforecast.datasets import fetch_dataset\n",
    "from skforecast.recursive import ForecasterRecursive\n",
    "from skforecast.model_selection import TimeSeriesFold, backtesting_forecaster\n",
    "from skforecast.plot import set_dark_theme"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">╭───────────────────────────────── <span style=\"font-weight: bold\">bike_sharing</span> ──────────────────────────────────╮\n",
       "│ <span style=\"font-weight: bold\">Description:</span>                                                                    │\n",
       "│ Hourly usage of the bike share system in the city of Washington D.C. during the │\n",
       "│ years 2011 and 2012. In addition to the number of users per hour, information   │\n",
       "│ about weather conditions and holidays is available.                             │\n",
       "│                                                                                 │\n",
       "│ <span style=\"font-weight: bold\">Source:</span>                                                                         │\n",
       "│ Fanaee-T,Hadi. (2013). Bike Sharing Dataset. UCI Machine Learning Repository.   │\n",
       "│ https://doi.org/10.24432/C5W894.                                                │\n",
       "│                                                                                 │\n",
       "│ <span style=\"font-weight: bold\">URL:</span>                                                                            │\n",
       "│ https://raw.githubusercontent.com/skforecast/skforecast-                        │\n",
       "│ datasets/main/data/bike_sharing_dataset_clean.csv                               │\n",
       "│                                                                                 │\n",
       "│ <span style=\"font-weight: bold\">Shape:</span> 17544 rows x 11 columns                                                  │\n",
       "╰─────────────────────────────────────────────────────────────────────────────────╯\n",
       "</pre>\n"
      ],
      "text/plain": [
       "╭───────────────────────────────── \u001b[1mbike_sharing\u001b[0m ──────────────────────────────────╮\n",
       "│ \u001b[1mDescription:\u001b[0m                                                                    │\n",
       "│ Hourly usage of the bike share system in the city of Washington D.C. during the │\n",
       "│ years 2011 and 2012. In addition to the number of users per hour, information   │\n",
       "│ about weather conditions and holidays is available.                             │\n",
       "│                                                                                 │\n",
       "│ \u001b[1mSource:\u001b[0m                                                                         │\n",
       "│ Fanaee-T,Hadi. (2013). Bike Sharing Dataset. UCI Machine Learning Repository.   │\n",
       "│ https://doi.org/10.24432/C5W894.                                                │\n",
       "│                                                                                 │\n",
       "│ \u001b[1mURL:\u001b[0m                                                                            │\n",
       "│ https://raw.githubusercontent.com/skforecast/skforecast-                        │\n",
       "│ datasets/main/data/bike_sharing_dataset_clean.csv                               │\n",
       "│                                                                                 │\n",
       "│ \u001b[1mShape:\u001b[0m 17544 rows x 11 columns                                                  │\n",
       "╰─────────────────────────────────────────────────────────────────────────────────╯\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>users</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date_time</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2011-01-01 00:00:00</th>\n",
       "      <td>16.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-01-01 01:00:00</th>\n",
       "      <td>40.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-01-01 02:00:00</th>\n",
       "      <td>32.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-01-01 03:00:00</th>\n",
       "      <td>13.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-01-01 04:00:00</th>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-02-11 11:00:00</th>\n",
       "      <td>64.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-02-11 12:00:00</th>\n",
       "      <td>71.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-02-11 13:00:00</th>\n",
       "      <td>110.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-02-11 14:00:00</th>\n",
       "      <td>84.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-02-11 15:00:00</th>\n",
       "      <td>74.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1000 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                     users\n",
       "date_time                 \n",
       "2011-01-01 00:00:00   16.0\n",
       "2011-01-01 01:00:00   40.0\n",
       "2011-01-01 02:00:00   32.0\n",
       "2011-01-01 03:00:00   13.0\n",
       "2011-01-01 04:00:00    1.0\n",
       "...                    ...\n",
       "2011-02-11 11:00:00   64.0\n",
       "2011-02-11 12:00:00   71.0\n",
       "2011-02-11 13:00:00  110.0\n",
       "2011-02-11 14:00:00   84.0\n",
       "2011-02-11 15:00:00   74.0\n",
       "\n",
       "[1000 rows x 1 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Downloading data\n",
    "# ==============================================================================\n",
    "data = fetch_dataset(\"bike_sharing\")\n",
    "data = data[['users']].iloc[:1000].copy()\n",
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Dates train: 2011-01-01 00:00:00 --- 2011-01-31 23:00:00  (n=744)\n",
      "Dates test : 2011-02-01 00:00:00 --- 2011-02-11 15:00:00  (n=256)\n"
     ]
    }
   ],
   "source": [
    "# Split train-test\n",
    "# ==============================================================================\n",
    "end_train = '2011-01-31 23:59:00'\n",
    "data_train = data.loc[: end_train, :]\n",
    "data_test  = data.loc[end_train:, :]\n",
    "\n",
    "print(f\"Dates train: {data_train.index.min()} --- {data_train.index.max()}  (n={len(data_train)})\")\n",
    "print(f\"Dates test : {data_test.index.min()} --- {data_test.index.max()}  (n={len(data_test)})\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 700x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot time series\n",
    "# ==============================================================================\n",
    "set_dark_theme()\n",
    "fig, ax = plt.subplots(figsize=(7, 3))\n",
    "data_train['users'].plot(ax=ax, label='train')\n",
    "data_test['users'].plot(ax=ax, label='test')\n",
    "ax.set_title('Number of users')\n",
    "ax.set_xlabel('')\n",
    "ax.legend();"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Forecaster"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create a forecaster and train it\n",
    "# ==============================================================================\n",
    "forecaster = ForecasterRecursive(\n",
    "                 estimator = Ridge(random_state=123),\n",
    "                 lags      = 24\n",
    "             )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "d549ebe979214405a7bd847bebc04681",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/11 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Backtesting predictions on test data\n",
    "# ==============================================================================\n",
    "cv = TimeSeriesFold(\n",
    "        steps              = 24,\n",
    "        initial_train_size = len(data_train),\n",
    "     )\n",
    "\n",
    "metric, predictions = backtesting_forecaster(\n",
    "                          forecaster = forecaster,\n",
    "                          y          = data['users'],\n",
    "                          cv         = cv,\n",
    "                          metric     = 'mean_squared_error'\n",
    "                      )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 700x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot predictions\n",
    "# ==============================================================================\n",
    "fig, ax = plt.subplots(figsize=(7, 3))\n",
    "data_test['users'].plot(ax=ax, label='test')\n",
    "predictions['pred'].plot(ax=ax, label='predictions')\n",
    "ax.set_xlabel('')\n",
    "ax.legend();"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The graph above shows that some predictions are negative."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>fold</th>\n",
       "      <th>pred</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2011-02-01 00:00:00</th>\n",
       "      <td>0</td>\n",
       "      <td>-23.337236</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-02-01 01:00:00</th>\n",
       "      <td>0</td>\n",
       "      <td>-17.691405</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-02-02 00:00:00</th>\n",
       "      <td>1</td>\n",
       "      <td>-5.243456</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-02-02 01:00:00</th>\n",
       "      <td>1</td>\n",
       "      <td>-19.363139</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-02-03 01:00:00</th>\n",
       "      <td>2</td>\n",
       "      <td>-6.441943</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-02-04 01:00:00</th>\n",
       "      <td>3</td>\n",
       "      <td>-10.579940</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-02-05 00:00:00</th>\n",
       "      <td>4</td>\n",
       "      <td>-6.026119</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-02-05 01:00:00</th>\n",
       "      <td>4</td>\n",
       "      <td>-21.396841</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-02-07 04:00:00</th>\n",
       "      <td>6</td>\n",
       "      <td>-3.412043</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-02-07 05:00:00</th>\n",
       "      <td>6</td>\n",
       "      <td>-3.701964</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-02-08 00:00:00</th>\n",
       "      <td>7</td>\n",
       "      <td>-17.045913</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-02-08 01:00:00</th>\n",
       "      <td>7</td>\n",
       "      <td>-13.233004</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-02-09 00:00:00</th>\n",
       "      <td>8</td>\n",
       "      <td>-25.315228</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-02-09 01:00:00</th>\n",
       "      <td>8</td>\n",
       "      <td>-24.743686</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-02-10 01:00:00</th>\n",
       "      <td>9</td>\n",
       "      <td>-5.704407</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-02-11 01:00:00</th>\n",
       "      <td>10</td>\n",
       "      <td>-11.758940</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     fold       pred\n",
       "2011-02-01 00:00:00     0 -23.337236\n",
       "2011-02-01 01:00:00     0 -17.691405\n",
       "2011-02-02 00:00:00     1  -5.243456\n",
       "2011-02-02 01:00:00     1 -19.363139\n",
       "2011-02-03 01:00:00     2  -6.441943\n",
       "2011-02-04 01:00:00     3 -10.579940\n",
       "2011-02-05 00:00:00     4  -6.026119\n",
       "2011-02-05 01:00:00     4 -21.396841\n",
       "2011-02-07 04:00:00     6  -3.412043\n",
       "2011-02-07 05:00:00     6  -3.701964\n",
       "2011-02-08 00:00:00     7 -17.045913\n",
       "2011-02-08 01:00:00     7 -13.233004\n",
       "2011-02-09 00:00:00     8 -25.315228\n",
       "2011-02-09 01:00:00     8 -24.743686\n",
       "2011-02-10 01:00:00     9  -5.704407\n",
       "2011-02-11 01:00:00    10 -11.758940"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Negative predictions\n",
    "# ==============================================================================\n",
    "predictions[predictions.pred < 0]"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Modeling time series in logarithmic scale"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Transform data into a logarithmic scale\n",
    "# =============================================================================\n",
    "data_log = np.log1p(data)\n",
    "data_train_log = np.log1p(data_train)\n",
    "data_test_log  = np.log1p(data_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "7b1d30bf7a324bcc8b34c01cabaa047f",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/11 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Create a forecaster and train it\n",
    "# ==============================================================================\n",
    "forecaster = ForecasterRecursive(\n",
    "                 estimator = Ridge(random_state=123),\n",
    "                 lags      = 24,\n",
    "             )\n",
    "\n",
    "# Backtesting predictions on test data\n",
    "# ==============================================================================\n",
    "# Since the data has been transformed outside the forecaster, the predictions\n",
    "# and metric are not in the original scale. They need to be transformed back.\n",
    "metric, predictions = backtesting_forecaster(\n",
    "                          forecaster = forecaster,\n",
    "                          y          = data_log['users'],\n",
    "                          cv         = cv,\n",
    "                          metric     = 'mean_squared_error'\n",
    "                      )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>fold</th>\n",
       "      <th>pred</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2011-02-01 00:00:00</th>\n",
       "      <td>0.0</td>\n",
       "      <td>7.936823</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-02-01 01:00:00</th>\n",
       "      <td>0.0</td>\n",
       "      <td>4.210682</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-02-01 02:00:00</th>\n",
       "      <td>0.0</td>\n",
       "      <td>3.009993</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-02-01 03:00:00</th>\n",
       "      <td>0.0</td>\n",
       "      <td>3.083922</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     fold      pred\n",
       "2011-02-01 00:00:00   0.0  7.936823\n",
       "2011-02-01 01:00:00   0.0  4.210682\n",
       "2011-02-01 02:00:00   0.0  3.009993\n",
       "2011-02-01 03:00:00   0.0  3.083922"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Revert the transformation\n",
    "# ==============================================================================\n",
    "predictions = np.expm1(predictions)\n",
    "predictions.head(4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Backtesting metric (test data): 1991.9332571760067\n"
     ]
    }
   ],
   "source": [
    "# Backtesting metric (test data)\n",
    "# ==============================================================================\n",
    "# The error metric is calculated once the transformation is reversed.\n",
    "metric = mean_squared_error(y_true=data_test['users'], y_pred=predictions['pred'])\n",
    "print(f\"Backtesting metric (test data): {metric}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 700x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot predictions\n",
    "# ==============================================================================\n",
    "fig, ax = plt.subplots(figsize=(7, 3))\n",
    "data_test['users'].plot(ax=ax, label='test')\n",
    "predictions['pred'].plot(ax=ax, label='predictions')\n",
    "ax.legend();"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Include a logarithmic transformer as part of the forecaster"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Using scikit-learn [FunctionTransformer](https://scikit-learn.org/stable/modules/generated/sklearn.preprocessing.FunctionTransformer.html) it is possible to include custom transformers in the forecaster object, for example, a logarithmic transformation. If the `FunctionTransformer` has an inverse function, the output of the predict method is automatically transformed back to the original scale."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "b9c645f638c64b338ba20ca292cc3938",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/11 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>mean_squared_error</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1991.933257</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   mean_squared_error\n",
       "0         1991.933257"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Create a custom transformer\n",
    "# =============================================================================\n",
    "import warnings\n",
    "warnings.filterwarnings(\n",
    "    \"ignore\",\n",
    "    message=\"X does not have valid feature names, but FunctionTransformer was fitted with feature names\"\n",
    ")\n",
    "transformer_y = FunctionTransformer(func=np.log1p, inverse_func=np.expm1, validate=True)\n",
    "\n",
    "# Create a forecaster and train it\n",
    "# ==============================================================================\n",
    "forecaster = ForecasterRecursive(\n",
    "                 estimator        = Ridge(random_state=123),\n",
    "                 lags             = 24,\n",
    "                 transformer_y    = transformer_y,\n",
    "                 transformer_exog = None\n",
    "             )\n",
    "forecaster.fit(data['users'])\n",
    "\n",
    "# Backtesting predictions on test data\n",
    "# ==============================================================================\n",
    "metric, predictions = backtesting_forecaster(\n",
    "                          forecaster = forecaster,\n",
    "                          y          = data['users'],\n",
    "                          cv         = cv,\n",
    "                          metric     = 'mean_squared_error'\n",
    "                      )\n",
    "\n",
    "# Since the transformation is included in the forecaster, predictions are\n",
    "# automatically transformed back into the original scale. And the metric is\n",
    "# calculated in the original scale.\n",
    "metric"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div class=\"admonition note\" name=\"html-admonition\" style=\"background: rgba(255,145,0,.1); padding-top: 0px; padding-bottom: 6px; border-radius: 8px; border-left: 8px solid #ff9100; border-color: #ff9100; padding-left: 10px; padding-right: 10px\">\n",
    "\n",
    "<p class=\"title\">\n",
    "    <i style=\"font-size: 18px; color:#ff9100; border-color: #ff1744;\"></i>\n",
    "    <b style=\"color: #ff9100;\"> <span style=\"color: #ff9100;\">&#9888;</span> Warning</b>\n",
    "</p>\n",
    "\n",
    "<code>FunctionTransformer</code> returns a userwarning un setting <code>validate=True</code>. To hide this warning use <code>warnings.filterwarnings(\"ignore\", message=\"X does not have valid feature names\")</code> before fitting or backtesting the forecaster.\n",
    "</div>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>fold</th>\n",
       "      <th>pred</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2011-02-01 00:00:00</th>\n",
       "      <td>0</td>\n",
       "      <td>7.936823</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-02-01 01:00:00</th>\n",
       "      <td>0</td>\n",
       "      <td>4.210682</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-02-01 02:00:00</th>\n",
       "      <td>0</td>\n",
       "      <td>3.009993</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-02-01 03:00:00</th>\n",
       "      <td>0</td>\n",
       "      <td>3.083922</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-02-01 04:00:00</th>\n",
       "      <td>0</td>\n",
       "      <td>3.865169</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     fold      pred\n",
       "2011-02-01 00:00:00     0  7.936823\n",
       "2011-02-01 01:00:00     0  4.210682\n",
       "2011-02-01 02:00:00     0  3.009993\n",
       "2011-02-01 03:00:00     0  3.083922\n",
       "2011-02-01 04:00:00     0  3.865169"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Backtest predictions\n",
    "# ==============================================================================\n",
    "predictions.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The same results are obtained as if the data were log-transformed outside the model. However, by including the log transformation in the model, all inverse transformations are handled automatically."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Usage of link functions"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "A forecaster with a linear model (scikit learn GammaRegressor) that uses a different link function is evaluated."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "bc25ef3e79514bbd8d9bc2b6e2f70f4f",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/11 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>mean_squared_error</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>3509.698436</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   mean_squared_error\n",
       "0         3509.698436"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Create a forecaster and train it\n",
    "# ==============================================================================\n",
    "forecaster = ForecasterRecursive(\n",
    "                 estimator = GammaRegressor(alpha=1, max_iter=100000),\n",
    "                 lags      = 20,\n",
    "             )\n",
    "\n",
    "# Backtesting predictions on test data\n",
    "# ==============================================================================\n",
    "metric, predictions = backtesting_forecaster(\n",
    "                          forecaster = forecaster,\n",
    "                          y          = data['users'],\n",
    "                          cv         = cv,\n",
    "                          metric     = 'mean_squared_error'\n",
    "                      )\n",
    "\n",
    "metric"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>fold</th>\n",
       "      <th>pred</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2011-02-01 00:00:00</th>\n",
       "      <td>0</td>\n",
       "      <td>6.685711</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-02-01 01:00:00</th>\n",
       "      <td>0</td>\n",
       "      <td>10.238550</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-02-01 02:00:00</th>\n",
       "      <td>0</td>\n",
       "      <td>11.950465</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-02-01 03:00:00</th>\n",
       "      <td>0</td>\n",
       "      <td>9.194277</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-02-01 04:00:00</th>\n",
       "      <td>0</td>\n",
       "      <td>6.372488</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     fold       pred\n",
       "2011-02-01 00:00:00     0   6.685711\n",
       "2011-02-01 01:00:00     0  10.238550\n",
       "2011-02-01 02:00:00     0  11.950465\n",
       "2011-02-01 03:00:00     0   9.194277\n",
       "2011-02-01 04:00:00     0   6.372488"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Backtest predictions\n",
    "# ==============================================================================\n",
    "predictions.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In this case the gamma estimator model performed poorly, but if we look to the negative results:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>fold</th>\n",
       "      <th>pred</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Empty DataFrame\n",
       "Columns: [fold, pred]\n",
       "Index: []"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Negative predictions\n",
    "# ======================================================================================\n",
    "predictions[predictions.pred < 0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 700x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot predictions\n",
    "# ==============================================================================\n",
    "fig, ax = plt.subplots(figsize=(7, 3))\n",
    "data_test['users'].plot(ax=ax, label='test')\n",
    "predictions['pred'].plot(ax=ax, label='predictions')\n",
    "ax.legend();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Usage of XGBoost objective functions"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now a XGBoost model is trained, but with the objective function set to `reg:gamma`, so that the output is a mean of the gamma distribution, which is defined for positive values only."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "fe55e25d64e9431b95df664bd5d74a18",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/11 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>mean_squared_error</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1256.619357</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   mean_squared_error\n",
       "0         1256.619357"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Create forecaster and train\n",
    "# ==============================================================================\n",
    "params = {\n",
    "    'tree_method': 'hist',\n",
    "    'objective': 'reg:gamma'\n",
    "}\n",
    "\n",
    "forecaster = ForecasterRecursive(\n",
    "                 estimator = XGBRegressor(**params),\n",
    "                 lags      = 24,\n",
    "             )\n",
    "\n",
    "# Backtesting predictions on test data\n",
    "# ==============================================================================\n",
    "metric, predictions = backtesting_forecaster(\n",
    "                          forecaster = forecaster,\n",
    "                          y          = data['users'],\n",
    "                          cv         = cv,\n",
    "                          metric     = 'mean_squared_error'\n",
    "                      )\n",
    "\n",
    "metric"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>fold</th>\n",
       "      <th>pred</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Empty DataFrame\n",
       "Columns: [fold, pred]\n",
       "Index: []"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Negative predictions\n",
    "predictions[predictions.pred < 0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 700x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot predictions\n",
    "# ==============================================================================\n",
    "fig, ax = plt.subplots(figsize=(7, 3))\n",
    "data_test['users'].plot(ax=ax, label='test')\n",
    "predictions['pred'].plot(ax=ax, label='predictions')\n",
    "ax.legend();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The forecaster's performance is better than using a Ridge estimator with a log-transformer, and no negative predictions are made."
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "skforecast_py12",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.12.11"
  },
  "toc": {
   "base_numbering": 1,
   "nav_menu": {},
   "number_sections": false,
   "sideBar": true,
   "skip_h1_title": true,
   "title_cell": "Tabla de contenidos",
   "title_sidebar": "Tabla de contenidos",
   "toc_cell": false,
   "toc_position": {
    "height": "calc(100% - 180px)",
    "left": "10px",
    "top": "150px",
    "width": "165px"
   },
   "toc_section_display": true,
   "toc_window_display": false
  },
  "varInspector": {
   "cols": {
    "lenName": 16,
    "lenType": 16,
    "lenVar": 40
   },
   "kernels_config": {
    "python": {
     "delete_cmd_postfix": "",
     "delete_cmd_prefix": "del ",
     "library": "var_list.py",
     "varRefreshCmd": "print(var_dic_list())"
    },
    "r": {
     "delete_cmd_postfix": ") ",
     "delete_cmd_prefix": "rm(",
     "library": "var_list.r",
     "varRefreshCmd": "cat(var_dic_list()) "
    }
   },
   "position": {
    "height": "144.391px",
    "left": "1478px",
    "right": "20px",
    "top": "126px",
    "width": "350px"
   },
   "types_to_exclude": [
    "module",
    "function",
    "builtin_function_or_method",
    "instance",
    "_Feature"
   ],
   "window_display": false
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
